def getExtent(self):
"""Returns the shape of the dataimage.
:Returns:
tuple: Tuple with the size in voxel/timepoints.
The order of dimensions is (x,y,z,t,u,v,w). If the image has less
dimensions than 7 the return tuple will be shortened accordingly.
Please note that the order of dimensions is different from the tuple
returned by calling `NiftiImage.data.shape`!
.. seealso::
:meth:`~nifti.format.NiftiFormat.getVolumeExtent`,
:meth:`~nifti.format.NiftiFormat.getTimepoints`,
:attr:`~nifti.format.NiftiFormat.extent`
"""
# wrap dim array in nifti image struct
dims_array = ncl.intArray_frompointer(self.__nimg.dim)
dims = [ dims_array[i] for i in range(8) ]
return tuple( dims[1:dims[0]+1] )
def _updateNimgFromArray(self, val):
"""Update all relevant items in the nimg struct to match a given
array's properties.
We can only savely modify the respective nimg items since the data
array is disconnected from the struct all the time.
.. warning::
This is an internal method. Neither its availability nor its API is
guarenteed.
"""
# convert dtype and store in struct
self.raw_nimg.datatype = Ndtype2niftidtype(val)
# wrap dims
dim = ncl.intArray_frompointer(self.raw_nimg.dim)
# make sure there are no zeros in the dim vector
# especially not in #4 as FSLView doesn't like that
target_dim = N.ones(7, dtype='int')
# reverse the array shape
target_dim[:len(val.shape)] = val.shape[::-1]
# set number of dims
dim[0] = len(val.shape)
# assign remaining dim vector
for i in range(7):
dim[i+1] = target_dim[i]
# expand dim vector
self.raw_nimg.ndim = dim[0]
self.raw_nimg.nx = dim[1]
self.raw_nimg.ny = dim[2]
self.raw_nimg.nz = dim[3]
self.raw_nimg.nt = dim[4]
self.raw_nimg.nu = dim[5]
self.raw_nimg.nv = dim[6]
self.raw_nimg.nw = dim[7]